Which NLP (Natural Language Processing) innovation first allowed major retailers to implement semantic search, enabling customers to find products using natural language queries instead of exact keywords?

The intersection of language technology and retail has transformed how brands communicate with customers. From multilingual e-commerce platforms to voice shopping assistants, language innovations have reshaped retail strategies worldwide. This trivia question explores a pivotal moment when linguistic technology fundamentally altered retail recommendation systems. Test your knowledge about how language processing revolutionized the shopping experience!

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Word2Vec (2013), which mapped words to vectors based on context, allowing retailers to understand semantic relationships between search terms and products
LSTM Networks (2005), which improved language memory capacity, enabling retailers to track customer preferences across multiple shopping sessions
PageRank Algorithm (1998), which ranked search results based on relevance, helping retailers prioritize product listings
Statistical Machine Translation (2001), which allowed retailers to automatically translate product descriptions for global markets